Victor Zhenyi Wang (王振懿) is an AI-governance researcher and a Ph.D. student at the University of California, Berkeley School of Information (Source: knightcolumbia.org). He is a co-author of A Conceptual Model to Guide AI Risk Governance Strategies (Knight First Amendment Institute, March 2026).
Background
Wang holds a Master's in Development Engineering from the Blum Center at UC Berkeley. His work centers on AI governance, "boundary objects," and the relationship between public and technical accounts of AI risk (Source: victorzhenyiwang.notion.site).
Research
Wang co-authored A Conceptual Model to Guide AI Risk Governance Strategies (Knight First Amendment Institute, March 16, 2026) with Deirdre K. Mulligan (lead) and Nik Marda; the paper is summarized at A Conceptual Model to Guide AI Risk Governance Strategies (Mulligan + Marda + Wang, Knight Columbia, March 16 2026) and underlies Sociotechnical AI Risk Governance. The framework introduces two methodological primitives: a harm/hazard distinction, under which harms are realized negative impacts and hazards are probabilities of future harm, used as a primitive for reasoning about AI risk; and a handoff lens, an analytic approach to the points where responsibility passes between people, institutions, and automated systems.
The paper argues that "accountable AI governance in the public interest requires a sociotechnical systems approach to the study and mitigation of AI risks," pushing back against model-centric risk framings (Source: knightcolumbia.org).
Relationships
- co-author-with: Deirdre K. Mulligan, Nik Marda (Knight Columbia 2026 framework)
- contributes-to: Sociotechnical AI Risk Governance
- related: A Conceptual Model to Guide AI Risk Governance Strategies (Mulligan + Marda + Wang, Knight Columbia, March 16 2026), Knight First Amendment Institute (Knight Columbia)